Handling ambiguity via input-output kernel learning

• المؤلفون الرئيسيون: Xu, Xinxing, Tsang, Ivor Wai-Hung, Xu, Dong
• مؤلفون آخرون: School of Computer Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2013
• الموضوعات: DRNTU::Engineering::Computer science and engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/99740; http://hdl.handle.net/10220/13014
• المؤسسة: Nanyang Technological University

Data ambiguities exist in many data mining and machine learning applications such as text categorization and image retrieval. For instance, it is generally beneficial to utilize the ambiguous unlabeled documents to learn a more robust classifier for text categorization under the semi-supervised lear...